Sheryl E. KIMES and Gary M. THOMPSON, Cornell University

An Evaluation of Heuristic Methods for Determining the
Best Table Mix in Full-Service Restaurants

Revenue management research seeks to find the revenue-maximizing mix of customer demand, while the capacity management literature focuses on matching supply and demand. However, little research has been done on the optimal mix of supply that maximizes revenue, which is the context for our investigation. Specifically, we examine the effectiveness of heuristic techniques for the full-service restaurant table mix problem. We found the optimal number of different size tables for a restaurant to maximize its value (revenue or contribution) generating potential. Using data from a 240-seat full-service restaurant, we established base-line performance using complete enumeration of the table mix alternatives. Three of the heuristics we evaluated are based on integer-programming models. We also evaluated two variants of a simulated annealing heuristic front-end on a restaurant simulator. The better of the simulated annealing heuristic variants yielded the optimal solution in seven of eight test problems, averaging within 0.1% of optimal. We also observed that altering the table mix on a daily basis increased performance by over